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A modular analysis of microglia gene expression, insights into the aged phenotype
BACKGROUND: Microglia are multifunctional cells that are key players in brain development and homeostasis. Recent years have seen tremendous growth in our understanding of the role microglia play in neurodegeneration, CNS injury, and developmental disorders. Given that microglia show diverse functio...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6396472/ https://www.ncbi.nlm.nih.gov/pubmed/30819113 http://dx.doi.org/10.1186/s12864-019-5549-9 |
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author | Cho, Christine E. Damle, Sagar S. Wancewicz, Edward V. Mukhopadhyay, Swagatam Hart, Christopher E. Mazur, Curt Swayze, Eric E. Kamme, Fredrik |
author_facet | Cho, Christine E. Damle, Sagar S. Wancewicz, Edward V. Mukhopadhyay, Swagatam Hart, Christopher E. Mazur, Curt Swayze, Eric E. Kamme, Fredrik |
author_sort | Cho, Christine E. |
collection | PubMed |
description | BACKGROUND: Microglia are multifunctional cells that are key players in brain development and homeostasis. Recent years have seen tremendous growth in our understanding of the role microglia play in neurodegeneration, CNS injury, and developmental disorders. Given that microglia show diverse functional phenotypes, there is a need for more precise tools to characterize microglial states. Here, we experimentally define gene modules as the foundation for describing microglial functional states. RESULTS: In an effort to develop a comprehensive classification scheme, we profiled transcriptomes of mouse microglia in a stimulus panel with 96 different conditions. Using the transcriptomic data, we generated fine-resolution gene modules that are robustly preserved across datasets. These modules served as the basis for a combinatorial code that we then used to characterize microglial activation under various inflammatory stimulus conditions. CONCLUSIONS: The microglial gene modules described here were robustly preserved, and could be applied to in vivo as well as in vitro conditions to dissociate the signaling pathways that distinguish acutely inflamed microglia from aged microglia. The microglial gene modules presented here are a novel resource for classifying and characterizing microglial states in health and disease. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-019-5549-9) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6396472 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-63964722019-03-13 A modular analysis of microglia gene expression, insights into the aged phenotype Cho, Christine E. Damle, Sagar S. Wancewicz, Edward V. Mukhopadhyay, Swagatam Hart, Christopher E. Mazur, Curt Swayze, Eric E. Kamme, Fredrik BMC Genomics Research Article BACKGROUND: Microglia are multifunctional cells that are key players in brain development and homeostasis. Recent years have seen tremendous growth in our understanding of the role microglia play in neurodegeneration, CNS injury, and developmental disorders. Given that microglia show diverse functional phenotypes, there is a need for more precise tools to characterize microglial states. Here, we experimentally define gene modules as the foundation for describing microglial functional states. RESULTS: In an effort to develop a comprehensive classification scheme, we profiled transcriptomes of mouse microglia in a stimulus panel with 96 different conditions. Using the transcriptomic data, we generated fine-resolution gene modules that are robustly preserved across datasets. These modules served as the basis for a combinatorial code that we then used to characterize microglial activation under various inflammatory stimulus conditions. CONCLUSIONS: The microglial gene modules described here were robustly preserved, and could be applied to in vivo as well as in vitro conditions to dissociate the signaling pathways that distinguish acutely inflamed microglia from aged microglia. The microglial gene modules presented here are a novel resource for classifying and characterizing microglial states in health and disease. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-019-5549-9) contains supplementary material, which is available to authorized users. BioMed Central 2019-02-28 /pmc/articles/PMC6396472/ /pubmed/30819113 http://dx.doi.org/10.1186/s12864-019-5549-9 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Cho, Christine E. Damle, Sagar S. Wancewicz, Edward V. Mukhopadhyay, Swagatam Hart, Christopher E. Mazur, Curt Swayze, Eric E. Kamme, Fredrik A modular analysis of microglia gene expression, insights into the aged phenotype |
title | A modular analysis of microglia gene expression, insights into the aged phenotype |
title_full | A modular analysis of microglia gene expression, insights into the aged phenotype |
title_fullStr | A modular analysis of microglia gene expression, insights into the aged phenotype |
title_full_unstemmed | A modular analysis of microglia gene expression, insights into the aged phenotype |
title_short | A modular analysis of microglia gene expression, insights into the aged phenotype |
title_sort | modular analysis of microglia gene expression, insights into the aged phenotype |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6396472/ https://www.ncbi.nlm.nih.gov/pubmed/30819113 http://dx.doi.org/10.1186/s12864-019-5549-9 |
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